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acm基础 数论 知识必备！很重要的基本功！ 有助于菜鸟入门！()

Image Indexing Using Color Correlogram

以心电信号为例，利用小波变换模极大重建原信号(Reconstruction of the original signal using wavelet transform modulus maxima)

haar小波变换 在图像配准中可以使用 进而进行基于小波金字塔的模板交互匹配(haar wavelet transform in image registration can be used to carry out based on wavelet pyramid interactive template matching)

最邻近插值的matlab实现代码，可以对图像进行插值，插值的方法为最邻近插值法(The nearest neighbor interpolation matlab code, image interpolation, interpolation methods nearest neighbor interpolation)

数字图像处理中的平滑和锐化（边缘检测）。包括1、添加椒盐、高斯噪声。2对噪声污染的图像分别使用邻域平均法、中值滤波法、K邻近平均法进行平滑。3对一幅图像利用Roberts梯度法、Sobel算子和拉普拉斯算子进行锐化，并比较结果。附处理源图像和处理结果截图。 (Digital image processing smoothing and sharpening (edge detection). Including 1, add salt and pepper, Gaussian noise. Two pairs of images were used noise pollution neighborhood average, median filtering, K close to the average method to smooth. 3 on an image using Roberts gradient method, Sobel operator and Laplacian sharpening, and compare the results. Laws dealing with the source image capture and processing results.)

1、对观测数据进行中心化，； 2、使它的均值为0，对数据进行白化—>Z； 3、选择需要估计的分量的个数m，设置迭代次数p<-1 4、选择一个初始权矢量（随机的W，使其维数为Z的行向量个数）； 5、利用迭代W(i,p)=mean(z(i,:).*(tanh((temp) *z)))-(mean(1-(tanh((temp)) *z).^2)).*temp(i,1)来学习W （这个公式是用来逼近负熵的） 6、用对称正交法处理下W 7、归一化W(:,p)=W(:,p)/norm(W(:,p)) 8、若W不收敛，返回第5步 9、令p=p+1，若p小于等于m,返回第4步 剩下的应该都能看懂了 基本就是基于负熵最大的快速独立分量分析算法(1, on the center of the observation data, 2, making a mean of 0, the data to whitening-> Z 3, select the number of components to be estimated m, setting the number of iterations p < -1 4, select an initial weight vector (random W, so that the Z dimension of the row vectors of numbers) 5, the use of iteration W (i, p) = mean (z (i, :).* (tanh ((temp) ' * z)))- (mean (1- (tanh ((temp)) ' * z). ^ 2)).* temp (i, 1) to learn W (This formula is used to approximate the negative entropy) 6 with symmetric orthogonal treatments W 7, normalized W (:, p) = W (:, p)/norm (W (:, p)) 8, if W does not converge, return to step 5 9 , so that p = p+1, if p less than or equal m, return to step 4 should be able to read the rest of the basic is based on negative entropy of the largest fast independent component analysis algorithm)

衡量图像去噪和SAR图像降斑效果的一些指标，psnr，snr，enl(enl（Equivalent number of looks）)

数字图像处理同态滤波器 数字图像处理 冈萨雷斯二版 p153例4.10(Homomorphic filter Digital Image Processing Digital Image Processing Gonzalez p153 cases 4.10)

图像重建算法当中的FDK、ART和TV算法，以及算法评估的SSIM和MSE的评估代码(FDK, ART and TV algorithms in image reconstruction algorithms, and the evaluation codes of SSM and MSE for algorithm evaluation)